signals and classification

39
SIGNALS AND SYSTEM SURAJ MISHRA SUMIT SINGH AMIT GUPTA PRATYUSH SINGH (E.C 2 ND YEAR ,MCSCET) 1

Upload: suraj-mishra

Post on 14-Dec-2014

1.317 views

Category:

Documents


1 download

DESCRIPTION

 

TRANSCRIPT

Page 1: Signals and classification

SIGNALS AND SYSTEM

SURAJ MISHRA

SUMIT SINGH

AMIT GUPTA

PRATYUSH SINGH

(E.C 2ND YEAR ,MCSCET) 1

Page 2: Signals and classification

2

Topics

Introduction Classification of Signals Some Useful Signal Operations Some useful signal models

Page 3: Signals and classification

3

Introduction

The concepts of signals and systems arise in a wide variety of areas:communications, circuit design, biomedical engineering, power systems, speech processing, etc.

Page 4: Signals and classification

4

What is a Signal?

SIGNAL A set of information or data. Function of one or more

independent variables. Contains information about the

behavior or nature of some phenomenon.

Page 5: Signals and classification

5

Examples of Signals

BRAIN WAVE

Page 6: Signals and classification

6

Examples of Signals

Stock Market data as signal (time series)

Page 7: Signals and classification

7

What is a System?

SYSTEMSignals may be processed further

by systems, which may modify them or extract additional from them.

A system is an entity that processes a set of signals (inputs) to yield another set of signals (outputs).

Page 8: Signals and classification

8

What is a System? (2)

A system may be made up of physical components, as in electrical or mechanical systems (hardware realization).

A system may be an algorithm that computes an outputs from an inputs signal (software realization).

Page 9: Signals and classification

9

Examples of signals and systems

Voltage (x1) and current (x2) as functions of time in an electrical circuit are examples of signals.

A circuit is itself an example of a system (T), which responds to applied voltages and currents.

Page 10: Signals and classification

10

Some Useful Signal Some Useful Signal ModelsModels

Page 11: Signals and classification

11

Signal Models: Unit Step Function

Continuous-Time unit step function, u(t):

u(t) is used to start a signal, f(t) at t=0 f(t) has a value of ZERO for t <0

Page 12: Signals and classification

12

Signal Models: Unit Impulse Function

A possible approximation to a unit impulse:An overall area that has been maintained at unity.

Multiplication of a function by an Impulse?

b(t) = 0; for all t0is an impulse function which the area is b.

Graphically, it is represented by an arrow "pointing to infinity" at t=0 with its length equal to its area.

Page 13: Signals and classification

13

Signal Models: Unit Impulse Function (3)

May use functions other than a rectangular pulse. Here are three example functions:

Note that the area under the pulse function must be unity.

Page 14: Signals and classification

14

Signal Models: Unit Ramp Function

Unit ramp function is defined by: r(t) = tu(t)

Where can it be used?

Page 15: Signals and classification

15

Signal Models: Exponential Function est

Most important function in SNS where s is complex in general, s = +j

Therefore,est = e(+j)t = etejt = et(cost + jsint)(Euler’s formula: ejt = cost + jsint)

If s = -j, est = e(-j)t = ete-jt = et(cost - jsint)

From the above, etcost = ½(est +e-st )

Page 16: Signals and classification

16

Signal Models: Exponential Function est (2)

Variable s is complex frequency. est = e(+j)t = etejt = et(cost + jsint)

est = e(-j)t = ete-jt = et(cost - jsint)etcost = ½(est +e-st )

There are special cases of est :1. A constant k = ke0t (s=0 =0,=0)

2. A monotonic exponential et (=0, s=)

3. A sinusoid cost (=0, s=j)

4. An exponentially varying sinusoid etcost (s= j)

Page 17: Signals and classification

17

Signals Classification

Signals may be classified into: 1. Continuous-time and Discrete-time signals 2. Deterministic and Stochastic Signal 3. Periodic and Aperiodic signals 4. Even and Odd signals 5. Energy and Power signals

Page 18: Signals and classification

18

Continuous v/S Discrete Signals

Continuous-timeA signal that is specified for everyvalue of time t.

Discrete-timeA signal that is specified only at discrete valuesof time t.

Page 19: Signals and classification

Deterministic v/s Stochastic Signal

Signals that can be written in any mathematical expression are called deterministic signal.

(sine,cosine..etc) Signals that cann’t be written in mathematical

expression are called stochastic signals. (impulse,noise..etc)

19

Page 20: Signals and classification

Periodic v/s Aperiodic Signals

Signals that repeat itself at a proper interval of time are called periodic signals.

Continuous-time signals are said to be periodic.

Signals that will never repeat themselves,and get over in limited time are called aperiodic or non-periodic signals.

20

Page 21: Signals and classification

21

Even v/s Odd Signals

Page 22: Signals and classification

22

Even v/s Odd Signals

A signal x(t) or x[n] is referred to as an even signal if CT: DT:

A signal x(t) or x[n] is referred to as an odd signal if CT: DT:

Page 23: Signals and classification

23

Even and Odd Functions: Properties

Property:

Area: Even signal:

Odd signal:

Page 24: Signals and classification

24

Even and Odd Components of a Signal (1)

Every signal f(t) can be expressed as a sum of even and odd components because

Example, f(t) = e-atu(t)

Page 25: Signals and classification

25

Signal with finite energy (zero power)

Signal with finite power (infinite energy)

Signals that satisfy neither property are referred as neither energy nor power signals

Energy v/s Power Signals

Page 26: Signals and classification

26

Size of a Signal, Energy (Joules)

Measured by signal energy Ex:

Generalize for a complex valued signal to: CT: DT:

Energy must be finite, which means

Page 27: Signals and classification

27

Size of a Signal, Power (Watts)

If amplitude of x(t) does not → 0 when t → ∞, need to measure power Px instead:

Again, generalize for a complex valued signal to: CT:

DT:

Page 28: Signals and classification

OPERATIONS ON SIGNALS

It includes the transformation of independent variables.

It is performed in both continuous and discrete time signals.

Operations that are performed are-

28

Page 29: Signals and classification

1.ADDITION &SUBSTRACTION

Let two signals x(t) and y(t) are given, Their addition will be,

z(t) = x(t) + y(t)

Their substraction will be,

z(t) = x(t) – y(t)

29

Page 30: Signals and classification

2.MULTIPLICATION OF SIGNAL BY A CONSTANT

If a constant ‘A’ is given with a signal x(t)

z(t) = A.x(t)

If A>1,it is an amplified signal. If A<1,it is an attenuated signal.

30

Page 31: Signals and classification

3.MULTIPLICATION OF TWO SIGNALS

If two signals x(t) and y(t) are given,than their multiplication will be

z(t) = x(t).y(t)

31

Page 32: Signals and classification

4.SHIFTING IN TIME

Let a signal x(t),than the signal x(t-T) represented a delayed version of x(t),which is delayed by T sec.

32

Page 33: Signals and classification

33

Signal Operations: Time Shifting

Shifting of a signal in time adding or subtracting the amount of the

shift to the time variable in the function. x(t) x(t–to)

to > 0 (to is positive value),signal is shifted to the right (delay).

to < 0 (to is negative value),signal is shifted to the left (advance).

x(t–2)? x(t) is delayed by 2 seconds. x(t+2)? x(t) is advanced by 2 seconds.

Page 34: Signals and classification

34

Signal Operations: Time Shifting (2)

Subtracting a fixed amount from the time variable will shift the signal to the right that amount.

Adding to the time variable will shift the signal to the left.

Page 35: Signals and classification

35

Signal Operations: Time Shifting

Shifting of a signal in time

Page 36: Signals and classification

5.COMPRESSION/EXPANSION OF SIGNALS

This is also known as ‘Time Scaling’ process. Let a signal x(t) is given,we will examine as

x(at)

where a =real number and how it is related to x(t) ?

36

Page 37: Signals and classification

Time Scaling

37

Page 38: Signals and classification

38

Signal Operations: Time Inversion

Reversal of the time axis, or folding/flipping the signal (mirror image) over the y-axis.

Page 39: Signals and classification

THANKS....................... FOR YOUR

ATTENTION !

39